Results 61 to 70 of about 38,147 (211)

Daily lake-level time series spectral analysis using EMD, VMD, EWT, and EFD

Journal of Water and Climate Change
This study investigates the dynamics of daily Urmia Lake level (ULL) changes using spectral analysis tools to discover fluctuating patterns in the ULL series.
Farhad Alizadeh, Kiyoumars Roushangar
doaj   +1 more source

To VMD, or not to VMD, in the quark-gluon plasma

, 1995
I review results on the shift of the $ρ$ meson mass at nonzero temperature in a gauged linear sigma model, under the assumption of strict vector meson dominance. (Based upon a talk presented at the International Workshop on "Chiral Dynamics in Hadrons and Nuclei", Seoul, Korea, Feb., 1995).
openaire   +2 more sources

THE ωρπ COUPLING IN THE VMD MODEL REVISITED [PDF]

International Journal of Modern Physics A, 2012
We determine the value of the ω-ρ-π mesons coupling (gωρπ), in the context of the vector meson dominance model, from radiative decays, the ω→3π decay width and the e+e-→3π cross-section. For the last two observables we consider the effect of either a heavier resonance (ρ′(1450)) or a contact term.
D. GARCÍA GUDIÑO, G. TOLEDO SÁNCHEZ
openaire   +1 more source

F10.7 Daily Forecast Using LSTM Combined With VMD Method

Space Weather
The F10.7 solar radiation flux is a well‐known parameter that is closely linked to solar activity, serving as a key index for measuring the level of solar activity. In this study, the Variational Mode Decomposition (VMD) and Long Short‐term Memory (LSTM)
Y. Hao, Jianyong Lu, Guangshuai Peng, Ming Wang, Jingyuan Li, G. Wei   +5 more
semanticscholar   +1 more source

An insight on VMD for diagnosing wind turbine blade faults using C4.5 as feature selection and discriminating through multilayer perceptron

Alexandria Engineering Journal, 2020
This paper presents a pioneer study of identifying the wind turbine blade condition based on its vibration pattern. The study used variational mode decomposition (VMD) for signal pre-processing.
A. Joshuva, R. Sathish Kumar, S. Sivakumar, G. Deenadayalan, R. Vishnuvardhan   +4 more
doaj   +1 more source

Responses of groundwater to precipitation variability and ENSO in the Vietnamese Mekong Delta

Hydrology Research, 2021
Groundwater is a critical component of water resources and has become the primary water supply for agricultural and domestic uses in the Vietnamese Mekong Delta (VMD).
Phong V. V. Le, Hai V. Pham, Luyen K. Bui, Anh N. Tran, Chien V. Pham, Giang V. Nguyen, Phuong A. Tran   +6 more
doaj   +1 more source

A dynamic prediction model of landslide displacement based on VMD–SSO–LSTM approach

Scientific Reports
Addressing the limitations of existing landslide displacement prediction models in capturing the dynamic characteristics of data changes, this study introduces a novel dynamic displacement prediction model for landslides.
Haiying Wang, Yang Ao, Chenguang Wang, Yingzhi Zhang, Xiaofeng Zhang   +4 more
semanticscholar   +1 more source

Intelligent Fault Diagnosis Method Based on VMD-Hilbert Spectrum and ShuffleNet-V2: Application to the Gears in a Mine Scraper Conveyor Gearbox

Italian National Conference on Sensors, 2023
This paper introduces a fault diagnosis method for mine scraper conveyor gearbox gears using motor current signature analysis (MCSA). This approach solves problems related to gear fault characteristics that are affected by coal flow load and power ...
Weibing Wang, Shuai Guo, Shuanfeng Zhao, Zhengxiong Lu, Zhizhong Xing, Zelin Jing, Zheng Wei, Yuan Wang   +7 more
semanticscholar   +1 more source

Optimization method for remaining life prediction of conventional circuit breaker based on deep learning

Diance yu yibiao
In the context of smart grid, aiming at the condition monitoring of conventional circuit breakers with complex mechanical actions, an optimization method for remaining life prediction of conventional circuit breaker based on deep learning is proposed ...
SUN Shuguang, WEI Shuo, WANG Jingqin, SHAO Xu, SUN Liang, GAO Hui   +5 more
doaj   +1 more source

Machine Learning Models Coupled with Variational Mode Decomposition: A New Approach for Modeling Daily Rainfall-Runoff

Atmosphere, 2018
Accurate modeling for nonlinear and nonstationary rainfall-runoff processes is essential for performing hydrologic practices effectively. This paper proposes two hybrid machine learning models (MLMs) coupled with variational mode decomposition (VMD) to ...
Youngmin Seo, Sungwon Kim, Vijay P. Singh   +2 more
doaj   +1 more source